




def        __UpperCAmelCase						(							lowerCamelCase_ :     int = 10  ,							lowerCamelCase_ :     int = 10_00  ,							lowerCamelCase_ :     bool = True  )       ->  int:







			"""simple docstring"""





			assert (
			    isinstance(lowerCamelCase_  ,							lowerCamelCase_  )
			    and isinstance(lowerCamelCase_  ,							lowerCamelCase_  )
			    and isinstance(lowerCamelCase_  ,							lowerCamelCase_  )
			), "Invalid type of value(s) specified to function!"

			if min_val > max_val:
						raise ValueError('Invalid value for min_val or max_val (min_value < max_value)'  )
			return min_val if option else max_val





def        __UpperCAmelCase						(							lowerCamelCase_ :     int  ,							lowerCamelCase_ :     int  )       ->  int:







			"""simple docstring"""





			return int((number_a + number_a) / 2  )





def        __UpperCAmelCase						(							lowerCamelCase_ :     int  ,							lowerCamelCase_ :     int  ,							lowerCamelCase_ :     int  )       ->  None:







			"""simple docstring"""





			assert (
			    isinstance(lowerCamelCase_  ,							lowerCamelCase_  ) and isinstance(lowerCamelCase_  ,							lowerCamelCase_  ) and isinstance(lowerCamelCase_  ,							lowerCamelCase_  )
			), 'argument values must be type of "int"'

			if lower > higher:
						raise ValueError('argument value for lower and higher must be(lower > higher)'  )

			if not lower < to_guess < higher:
						raise ValueError(
						    'guess value must be within the range of lower and higher value'  )

			def answer(lowerCamelCase_ :     int  ) -> str:
						if number > to_guess:
									return "high"
						elif number < to_guess:
									return "low"
						else:
									return "same"

			print('started...'  )

			SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      lower
			SCREAMING_SNAKE_CASE_   : Dict					  =      higher

			SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      []

			while True:
						SCREAMING_SNAKE_CASE_   : str					  =      get_avg(lowerCamelCase_  ,							lowerCamelCase_  )
						last_numbers.append(lowerCamelCase_  )

						if answer(lowerCamelCase_  ) == "low":
									SCREAMING_SNAKE_CASE_   : List[Any]					  =      number
						elif answer(lowerCamelCase_  ) == "high":
									SCREAMING_SNAKE_CASE_   : List[Any]					  =      number
						else:
									break

			print(F'guess the number : {last_numbers[-1]}'  )
			print(F'details : {last_numbers!s}'  )





def        __UpperCAmelCase						(							)       ->  None:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Tuple					  =      int(input('Enter lower value : '  ).strip()  )
			SCREAMING_SNAKE_CASE_   : List[Any]					  =      int(input('Enter high value : '  ).strip()  )
			SCREAMING_SNAKE_CASE_   : Dict					  =      int(input('Enter value to guess : '  ).strip()  )
			guess_the_number(lowerCamelCase_  ,							lowerCamelCase_  ,							lowerCamelCase_  )


if __name__ == "__main__":
						main()










'''simple docstring'''






import math

import tensorflow as tf
from packaging import version






def   __A    (				a_    :	List[Any]						):
		lowerCAmelCase  :     Any       						= tf.convert_to_tensor(a_						)
		lowerCAmelCase  :     List[Any]       						= 0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0						)   ,x.dtype						)						))

		return x * cdf






def   __A    (				a_    :	int						):
		lowerCAmelCase  :     Dict       						= tf.convert_to_tensor(a_						)
		lowerCAmelCase  :     int       						= tf.cast(math.pi   ,x.dtype						)
		lowerCAmelCase  :     Dict       						= tf.cast(0.0_4_4_7_1_5   ,x.dtype						)
		lowerCAmelCase  :     Dict       						= 0.5 * (1.0 + tf.tanh(tf.sqrt(2.0 / pi						) * (x + coeff * tf.pow(a_   ,3						))						))

		return x * cdf






def   __A    (				a_    :	Union[str, Any]						):
		lowerCAmelCase  :     Any       						= tf.convert_to_tensor(a_						)

		return x * tf.tanh(tf.math.softplus(a_						)						)






def   __A    (				a_    :	List[str]						):
		lowerCAmelCase  :     Dict       						= tf.convert_to_tensor(a_						)
		lowerCAmelCase  :     Any       						= tf.cast(0.0_4_4_7_1_5   ,x.dtype						)
		lowerCAmelCase  :     Optional[int]       						= tf.cast(0.7_9_7_8_8_4_5_6_0_8   ,x.dtype						)

		return 0.5 * x * (1.0 + tf.tanh(x * coeffa * (1.0 + coeffa * x * x)						))






def   __A    (				a_    :	Union[str, Any]						):
		lowerCAmelCase  :     Optional[int]       						= tf.convert_to_tensor(a_						)
		lowerCAmelCase  :     List[Any]       						= tf.cast(1.7_0_2   ,x.dtype						)
		return x * tf.math.sigmoid(coeff * x						)






def   __A    (				a_    :	List[Any]						):
		return tf.clip_by_value(_gelu(a_						)   ,-1_0   ,1_0						)






def   __A    (				a_    :	List[Any]   ,a_    :	List[Any]=-1						):
		lowerCAmelCase						,		lowerCAmelCase  :     Optional[int]       						= tf.split(a_   ,2   ,axis=a_						)
		return a * tf.math.sigmoid(a_						)


if version.parse(tf.version.VERSION) >= version.parse("""2.4"""):






					def   __A    (				a_    :	Optional[Any]						):
							return tf.keras.activations.gelu(a_   ,approximate=a_						)

					lowerCAmelCase									=   tf.keras.activations.gelu

					lowerCAmelCase									=   approximate_gelu_wrap
else:
					lowerCAmelCase									=   _gelu
					lowerCAmelCase									=   _gelu_new


lowerCAmelCase									=   {
    """gelu""": gelu,
    """gelu_10""": gelu_aa,
    """gelu_fast""": gelu_fast,
    """gelu_new""": gelu_new,
    """glu""": glu,
    """mish""": mish,
    """quick_gelu""": quick_gelu,
    """relu""": tf.keras.activations.relu,
    """sigmoid""": tf.keras.activations.sigmoid,
    """silu""": tf.keras.activations.swish,
    """swish""": tf.keras.activations.swish,
    """tanh""": tf.keras.activations.tanh,
}






def   __A    (				a_    :	int						):
		if activation_string in ACTaFN:
				return ACTaFN[activation_string]
		else:
				raise KeyError(f'''function {activation_string} not found in ACT2FN mapping {list(ACTaFN.keys()						)}'''						)



